Exact(2)
We first filtered the datasets down to approximately 10% of total genes (800 genes for dataset I, 2000 for dataset II, and 4000 for dataset III) based on Median Absolute Deviation MADD).
Thus, we filtered the datasets with high N/A rates before performing other survival analyses.
Similar(58)
In particular, we filtered the dataset to include only SNPs with at least 3 HA reads and a HA ratio of at least 0.2.
Since we were specifically interested in cryptic internal initiation of transcription, we focused on Cluster 2 and filtered the dataset for genes with an ORF that was represented by two or more probes.
We then filtered the dataset of significant loci and retained only genes where at least one of the orthologous contigs had >10 mapped reads.
To explore this further and to avoid any correlation between protein detection and experimental run, we filtered the dataset for proteins that were quantified in every sample.
Metta and Schlötterer [ 21] further filtered the dataset by several criteria such as high coverage between orthologous sequence alignments and intron absence to control the data quality (filtered out 26 cases) [ 21].
Next, we filtered the dataset to keep chains that are at most 30% similar with each other (to evenly sample the sequence space) and removed proteins that had any REMARK 465 annotation, i.e. any annotated disorder.
After carefully pruning and filtering the datasets, all the datasets were clustered (see Methods section) to avoid biased results due to overrepresentation of similar molecules.
The resultant output images were used to manually filter the datasets by deleting erroneously identified object sets caused by image artefacts or overlapping cells.
A number of rules were used to filter the dataset.
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